Abstract #4953

A New Multi-Atlas Selection Strategy for Zone Segmentation of the Prostate

Michela Antonelli¹, Edward W Johnston ², Manuel Jorge Cardoso¹, Benoit Presles¹, Shonit Punwani*², and Sebastien Ourselin*^1,3

¹Translational Imaging Group, CMIC, University College London, London, United Kingdom, ²Academic Radiology, University College London Centre for Medical Imaging, London, UK, ³Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK

Automatic segmentation of the prostate into peripheral and transition zones is paramount in developing computer aided diagnosis systems for prostate cancer diagnosis, as cancer behaves differently in each zone. We propose a multi-atlas based segmentation (MAS) algorithm characterized by a new atlas selection strategy: the performance of a subset of atlases is evaluated considering how well that subset segments the image that is most similar to the target image. Comparison of our method with three other MAS algorithms on fifty-five patients shows a statistically significant improvement on the segmentation accuracy.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.